Simple but accurate GCM-free approach for quantifying anthropogenic climate change

Abstract:

We are so used to analysing the climate with the help of giant computer models (GCM’s) that it is easy to get the impression that they are indispensable. Yet anthropogenic warming is so large (roughly 0.9^oC) that it turns out that it is straightforward to quantify it with more empirically based methodologies that can be readily understood by the layperson. The key is to use the CO₂ forcing as a linear surrogate for all the anthropogenic effects from 1880 to the present (implicitly including all effects due to Greenhouse Gases, aerosols and land use changes). To a good approximation, double the economic activity, double the effects. The relationship between the forcing and global mean temperature is extremely linear as can be seen graphically and understood without fancy statistics, [Lovejoy, 2014a] (see the attached figure and http://www.physics.mcgill.ca/~gang/Lovejoy.htm). To an excellent approximation, the deviations from the linear forcing - temperature relation can be interpreted as the natural variability. For example, this direct - yet accurate approach makes it graphically obvious that the “pause” or “hiatus” in the warming since 1998 is simply a natural cooling event that has roughly offset the anthropogenic warming [Lovejoy, 2014b].

Rather than trying to prove that the warming is anthropogenic, with a little extra work (and some nonlinear geophysics theory and pre-industrial multiproxies) we can disprove the competing theory that it is natural. This approach leads to the estimate that the probability of the industrial scale warming being a giant natural fluctuation is ≈0.1%: it can be dismissed. This destroys the last climate skeptic argument – that the models are wrong and the warming is natural. It finally allows for a closure of the debate.

In this talk we argue that this new, direct, simple, intuitive approach provides an indispensable tool for communicating – and convincing – the public of both the reality and the amplitude of anthropogenic warming.

References

Lovejoy, S. (2014a), Scaling fluctuation analysis and statistical hypothesis testing of anthropogenic warming, Climate Dynamics, 42, 2339-2351 doi: 10.1007/s00382-014-2128-2.

Lovejoy, S. (2014b), Return periods of global climate fluctuations and the pause, Geophys. Res. Lett., 41, 4704-4710 doi: doi: 10.1002/2014GL060478.